There are many potential military and commercial applications for improved (e.g., faster-responding, longer-range, more accurate, and economical) passive magnetic anomaly sensing-based surveillance systems that can detect, localize, classify, and track magnetic objects (e.g., as large as naval vessels, motor vehicles, etc., or as small as person-borne weapons, etc.) moving through a region of interest that can span over hundreds or thousands of square meters. The word “passive” indicates that the magnetic sensing system does not produce magnetic anomaly fields but only detects (and processes) the magnetic anomaly field that emanates from an object's inherent magnetic dipole signature. The magnetic dipole signatures stem from ferrous materials that are contained in the physical structure of an object.
In general, passive magnetic anomaly sensing-based systems for magnetic localization and classification of magnetic objects measure and analyze the magnetic induction fields that emanate from the objects. Magnetic localization is based on the fact that, at sensor-to-object distances greater than about twice the largest dimension of an object, the fields can be mathematically described by the magnetic dipole equation that relates the object's vector magnetic field components to the vector components of the object's position in space and its vector magnetic dipole moment. The object's magnetic dipole vector depends on the size, shape, orientation and magnetic permeability of the ferrous materials (i.e., iron, most steels, nickel, etc.) contained within the object. Thus, measurements of an object's magnetic dipole moment provide “magnetic signature” data that can be used to magnetically classify the object.
The use of passive magnetic sensors for accurate localization of magnetic objects generally involves an application of the magnetostatic dipole equation to magnetic field data measured by the sensors. The dipole equation relates three Cartesian (XYZ) components of an object's magnetic anomaly field at a given point in space to the three XYZ components of the point (relative to the object position) and the three XYZ components of the object's magnetic dipole vector. Therefore, in accordance with the magnetostatic dipole equation, the process of magnetic localization and classification of a magnetically polarized object requires measurement of magnetic anomaly field components to determine six unknown quantities; namely, three XYZ components of object position and three XYZ components of the object's magnetic signature vector. That is, the localization/classification process requires the measurement of at least six independent field quantities in order to determine the aforementioned six unknown object parameters.
A system for accurate “detection, localization, classification, and tracking” (DLCT) of moving magnetic objects should take into account the fact that a ferrous object's dipole moment signature typically will change as the object moves/rotates through the Earth's magnetic field. Thus, for moving objects, the DLCT process is complicated by the fact that a ferrous object's magnetic signatures will be continuously changing in magnitude and direction as the object's orientation in the Earth's magnetic field changes. (If the moving object is a permanent magnet only the direction of its magnetic dipole signature will change; however, the magnitude of its magnetic signature will remain constant even while the object rotates in the Earth's field.)
Conventional prior art magnetic sensor systems for standoff DLCT of magnetic objects typically use individual field and/or gradient component measurements and least squares methods or matrix inversion processes to simultaneously solve the magnetic dipole equation (and/or its gradients) for an object's vector position in space and magnetic dipole moment. However, because of the complexities of the dipole equation, the symmetries (i.e., lack of uniqueness) of magnetic anomaly field components, and the complexities introduced by motion-dependent changes in magnetic signature parameters, the conventional approach can result in multiple incorrect solutions (often denoted as “ghosts”) for an object's location. The correct solution can be determined by analyzing a time series of magnetic field data. However, this process can limit the speed of a conventional magnetic sensor's effective DLCT response. Also, the conventional approach's accuracy can be severely degraded if the object's motion results in its magnetic dipole signature changing during the field measurement/data collection process.
In order to overcome the limitations of conventional prior art magnetic sensing systems a unique magnetic scalar triangulation and ranging (i.e., magnetic STAR or MagSTAR) technology has been developed for high speed DLC of magnetic objects. The MagSTAR approach uses gradient tensor magnitudes (aka “contractions”) and/or anomaly field magnitudes to perform unambiguous “ghost-free” localization of magnetic objects. Each data sample collected by a MagSTAR sensor contains at least six independent channels of field or gradient info; and so the MagSTAR process allows complete point-by-point determination of object location and magnetic dipole signature. Therefore, the MagSTAR approach has a great advantage over prior art in that it can locate and track a magnetic object even while the object's magnetic signature is changing. In particular, means and methods for applying the MagSTAR approach for high-speed precision localization and tracking of moving magnetic objects are described in U.S. Pat. No. 7,342,399 (the '399 patent hereinafter) and patent application Ser. No. 12/383,083 (the '083 application hereinafter), filed Mar. 12, 2009. The '399 patent and the '083 application disclose unique magnetic sensing-based systems and methods that process data from rigid arrays of four or more vector triaxial magnetometers (TM) in unique, ghost-free MagSTAR algorithms for precision, high-speed localization, tracking and classification of magnetic objects. The '399 patent and the '083 application have unique advantages in that they can provide very accurate tracking of magnetic objects even while their magnetic dipole signatures are changing due to their motion in the earth's magnetic field.
However, the relatively short range, complexity, expense, and power requirements of the multi-TM, gradient-sensing embodiments of the '399 patent may not be optimal for many large-region surveillance applications. The means and methods for DLCT of moving objects taught in the '083 application overcome many of the limitations of the '399 patent by using less complex embodiments to process relatively longer-range magnetic anomaly field magnitudes. Nevertheless, the multi-TM embodiments of the '083 application may still be more complex and, therefore, more expensive than desirable for a magnetic surveillance system that must be able to observe a large area.